diff --git a/proj2022/prec_recall.py b/proj2022/prec_recall.py
new file mode 100755
index 0000000..f81c325
--- /dev/null
+++ b/proj2022/prec_recall.py
@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+import numpy as np
+import glob
+import os
+import pandas as pd
+
+DIR: str = os.path.dirname(os.path.realpath(__file__))
+IN_DIR: str = DIR + '/clustering'
+OUT_DIR: str = DIR + ''
+
+
+def intrapairs(path: str) -> set[set[str, str]]:
+    df = pd.read_csv(path)
+    clusters: list[list[str]] = df.groupby(
+        'cluster').agg(list).iloc[:, 0].values
+
+    intrapairs: set[set[str]] = set()  # inner sets always contain 2 elements
+    for cluster in clusters:
+        for i, e1 in enumerate(cluster):
+            for j in range(i + 1, len(cluster)):
+                e2 = cluster[j]
+                intrapairs.add(frozenset((e1, e2,)))
+    return intrapairs
+
+
+def main():
+    filelist = glob.glob(IN_DIR + '/*_groundtruth.csv')
+    for f in filelist:
+        clazz_name = os.path.basename(f)
+        clazz_name = clazz_name[:clazz_name.rfind('_groundtruth.csv')]
+        print(clazz_name)
+
+        ground_pairs = intrapairs(f)
+        for method in ['kmeans', 'hierarchical']:
+            cluster_pairs = intrapairs(
+                IN_DIR + '/' + clazz_name + '_' + method + '.csv')
+
+            n_common = len(ground_pairs.intersection(cluster_pairs))
+            precision = n_common / len(cluster_pairs)
+            recall = n_common / len(ground_pairs)
+
+            print(method + " precision: " + str(precision))
+            print(method + " recall: " + str(recall))
+
+        print()
+
+
+if __name__ == '__main__':
+    main()